In this paper, we present an easily understandable framework for solving arithmetic word problems. We hope that this will motivate to try out different techniques to help students understand word problem solving better.
In our approach, we have predefined action frames performing arithmetic operations. This task can be learned which action frame does what operation. The frame identification module can be improved by increasing its accuracy. We intent to increase the training data size by bootstrapping [1]}. Word embeddings can be used to find similar verbs. We rely on parser's output to fill the frame slots, we could explore the use of computation parsing instead of linguistic parsing. We could also integrate a co-reference and anaphora resolution module into our system as it is not handled in the current set-up. The learning of the question types and slots can also explored.
